What you’ll learn-51.5 hours
- Master Python for AI: Write efficient Python code, essential for AI and ML programming tasks.
- Data Preprocessing Skills: Prepare, clean, and transform data to enhance model performance.
- Statistical Knowledge: Apply core statistics to understand data patterns and inform decisions.
- Build Machine Learning Models: Develop and fine-tune ML models for classification, regression, and clustering.
- Deep Learning Proficiency: Design and train neural networks, including CNNs and RNNs, for image and sequence tasks.
- Utilize Transfer Learning: Adapt pre-trained models to new tasks, saving time and resources.
- Deploy ML Models with APIs: Create scalable APIs to serve ML models in real-world applications.
- Containerize with Docker: Package models for portable deployment across environments.
- Monitor and Maintain Models: Track model performance, detect drift, and implement retraining pipelines.
- Complete ML Lifecycle: Master end-to-end AI project skills, from data to deployment and ongoing maintenance.
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